Insurance providers generally monitor and track risk events such as hurricanes, earthquakes, tornadoes, wildfires, riots, unrest, hail events, volcanic eruptions, etc. that impact their products (e.g., insurance policies). A system of monitoring events that affect the state of a set of insurance policies may include an application that provides mapping of risk event related data based on information collected from multiple sources. Thus, for example, where a tornado is occurring or has occurred, data on the tornado event may be mapped to a geographic area. In this manner, an insurance provider or other interested party may be able to visualize and gauge its risk exposure via a map. Such a system may be called a mapping system or an impact-on-demand system.
A data collection and data management component may be implemented to manage data upon which the impact-on-demand system operates. For example, a worthwhile feature of such an event/risk mapping system may be the ability to accumulate and incorporate new data relating to the event from multiple sources in an efficient manner to enable basic mapping features such as real-time tracking, and on-demand report generation. However, managing the received data from multiple disparate sources having different formats can be difficult. Moreover, creating certain views based on dynamic data acquisition may require ad-hoc or on-the-fly re-organization of data. Further, in a system in which available data combinations are changing, an efficient process may be needed to recognize when certain fields or combinations of fields are available so that further data manipulation can be more efficient.